DL4KG 2023
Deep Learning for Knowledge Graphs 2023

Table of Contents

• Preface
  Summary: There were 9 papers submitted for peer-review to this workshop. Out of these, 7 papers were accepted for this volume.

Papers

• Location Query Answering Using Box Embeddings
  Eleni Tsalapati , Markos Iliakis , Manolis Koubarakis
• Knowledge Graph Injection for Reinforcement Learning
  Robert Wardenga , Liubov Kovriguina , Dmitrii Pliukhin , Daniil Radyush , Ivan SmoliakoV , Yuan Xue , Henrik Müller , Aleksei Pismerov , Dmitry Mouromtsev , Daniel Kudenko
• Benchmarking the Abilities of Large Language Models for RDF Knowledge Graph Creation and Comprehension: How Well Do LLMs Speak Turtle?
  Johannes Frey , Lars-Peter Meyer , Natanael Arndt , Felix Brei , Kirill Bulert
• Enhancing Large Language Models with Knowledge Graphs for Classification Tasks in the Tourism Domain
  Andrea Cadeddu , Alessandro Chessa , Vincenzo De Leo , Gianni Fenu , Enrico Motta , Francesco Osborne , Diego Reforgiato , Angelo Salatino , Luca Secchi
• Universal Preprocessing Operators for Embedding Knowledge Graphs with Literals
  Patryk Preisner , Heiko Paulheim
• NNKGC: Improving Knowledge Graph Completion with Node Neighborhoods
  Irene Li , Boming Yang
• Enhancing Scholarly Understanding: A Comparison of Knowledge Injection Strategies in Large Language Models
  Vincenzo De Leo , Andrea Cadeddu , Alessandro Chessa , Gianni Fenu , Enrico Motta , Francesco Osborne , Diego Reforgiato , Angelo Salatino , Luca Secchi